Abstract: This paper proposes a data collaboration analysis framework for distributed data sets. The proposed framework involves centralized machine learning while the original data sets and models remain distributed over a number ...

Abstract: This paper explores the problem of data collaboration in health care, which is the one of the critical infrastructure sectors designated by the Department of Home Security. Limitations to data sharing in health care obstruct ...

Abstract: Detecting anomalies is an important and challenging task for many applications. In recent years, spectral methods have been proposed to detect anomalous subgraphs embedded into a background graph using eigenvectors ...